Search results for: cancer systems biology

Authors: Adinarayana Gorajana, Venkata Srikanth Meka, Sanjay Garg, Lim Sue May

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This study was designed to evaluate and enhance the solubility of poorly soluble drug, docetaxel through solid dispersion (SD) technique prepared using freeze drying method. Docetaxel solid dispersions were formulated with Soluplus in different weight ratios. Freeze drying method was used to prepare the solid dispersions. Solubility of the solid dispersions were evaluated respectively and the optimized of drug-solubilizers ratio systems were characterized with different analytical methods like Differential scanning calorimeter (DSC), Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) to confirm the formation of complexes between drug and solubilizers. The solubility data revealed an overall improvement in solubility for all SD formulations. The ternary combination 1:5:2 gave the highest increase in solubility that is approximately 3 folds from the pure drug, suggesting the optimum drug-solubilizers ratio system. This data corresponds with the DSC and SEM analyses, which demonstrates presence of drug in amorphous state and the dispersion in the solubilizers in molecular level. The solubility of the poorly soluble drug, docetaxel was enhanced through preparation of solid dispersion formulations employing freeze drying method. Solid dispersion with multiple carrier system shows better solubility compared to single carrier system.

Keywords: docetaxel, freeze drying, soluplus, solid dispersion technique

Procedia PDF Downloads 503

Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Soofia Malik

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The purpose of this study is to develop an instrument to measure undergraduate students’ attitudes toward mathematics (MAT) and to assess the data collected from the instrument for validity and reliability. The instrument is developed using five subscales: anxiety, enjoyment, self-confidence, value, and technology. The technology dimension is added as the fifth subscale of attitude toward mathematics because of the recent trend of incorporating online homework in mathematics courses as well as due to heavy reliance of higher education on using online learning management systems, such as Blackboard and Moodle. The sample consists of 163 (M = 82, F = 81) undergraduates enrolled in College Algebra course in the summer 2017 semester at a university in the USA. The data is analyzed to answer the research question: if and how do undergraduate students’ attitudes toward mathematics load using Principal Components Analysis (PCA)? As a result of PCA, three subscales emerged namely: anxiety/self-confidence scale, enjoyment, and value scale. After deleting the last five items or the last two subscales from the initial MAT scale, the Cronbach’s alpha was recalculated using the scores from 20 items and was found to be α = .95. It is important to note that the reliability of the initial MAT form was α = .93. This means that employing the final MAT survey form would yield consistent results in repeated uses. The final MAT form is, therefore, more reliable as compared to the initial MAT form.

Keywords: college algebra, Cronbach's alpha reliability coefficient, Principal Components Analysis, PCA, technology in mathematics

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy

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Authors: Ankit Agarwal

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Background: To develop a fully indigenous equipment which is an innovation in critical care, which can effectively scavenge contaminated ICU ventilator air. Objectives: Infection control in ICUs is a concern the world over. Various modalities from simple hand hygiene to costly antibiotics exist. However, one simple and scientific fact has been unnoticed till date, that the air exhaled by patients harboring MDR and other microorganisms, is released by ventilators into ICU atmosphere itself. This increases infection in ICU atmosphere and poses risk to other patients. Material and Methods: Some parts of the ventilator are neither disposable nor sterilizable. Over time, microorganisms accumulate in ventilator and act as a source of infection and also contaminate ICU air. This was demonstrated by exposing microbiological culture plates to air from expiratory port of ventilator, whereby dense growth of pathogenic microorganisms was observed. The present prototype of the equipment is totally self-made. It has a mechanism of controlled negative pressure, active and passive systems and various alarms and is versatile to be used with any ventilator. Results: This equipment captures the whole of contaminated exhaled air from the expiratory port of the ventilator and directs it out of the ICU space. Thus, it does not allow contaminated ventilator air to release into the ICU atmosphere. Therefore, there is no chance of exposure of other patients to contaminated air. Conclusion: The equipment is first of its kind the world over and is already under patent process. It has rightly been called ICU Ventilator Air Removal System (ICU VARS). It holds a chance that this technique will gain widespread acceptance shall find use in all the ventilators in most of the ICUs throughout the world.

Keywords: innovative, ICU Infection Control, microorganism, negative pressure

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Authors: Bhaumik Tyagi, Mandeep Kaur, Kanika Singla

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The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays, where malicious codes are injected into the system through user input fields by illicit users, which leads to data leakage in the worst scenarios. Besides, quantum attacks are also there which manipulate the transactional data. In order to deal with all the above-mentioned attacks, integration of blockchain, convolutional neural network (CNN), and Quantum Key Distribution is done in this very research. The utilization of blockchain technology in e-voting applications is not a novel concept. But privacy and security issues are still there in a public and private blockchains. To solve this, the use of a hybrid blockchain is done in this research. This research proposed cryptographic signatures and blockchain algorithms to validate the origin and integrity of the votes. The convolutional neural network (CNN), a normalized version of the multilayer perceptron, is also applied in the system to analyze visual descriptions upon registration in a direction to enhance the privacy of voters and the e-voting system. Quantum Key Distribution is being implemented in order to secure a blockchain-based e-voting system from quantum attacks using quantum algorithms. Implementation of e-voting blockchain D-app and providing a proposed solution for the privacy of voters in e-voting using Blockchain, CNN, and Quantum Key Distribution is done.

Keywords: hybrid blockchain, secure e-voting system, convolutional neural networks, quantum key distribution, one-time pad

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Authors: Micheal O. Alabi

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Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.

Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing

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Authors: Aicha Bouhlala, Sabah Chettibi

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A systematic investigation on structural, electronic, and magnetic properties of Ce₀.₇₅A₀.₂₅O₂ (A = W, Mo) is performed using first-principles calculations within the framework Full-Potential Linear Augmented Plane Wave (FP-LAPW) method based on the Density Functional Theory (DFT). The exchange-correlation potential has been treated using the generalized gradient approximation (WC-GGA) developed by Wu-Cohen. The host compound CeO2 was doped with transition metal atoms W and Mo in the doping concentration of 25% to replace the Ce atom. In structural properties, the equilibrium lattice constant is observed for the W-doped CeO₂ compound which exists within the value of 5.314 A° and the value of 5.317 A° for Mo-doped CeO2. The present results show that Ce₀.₇₅A₀.₂₅O₂ (A=W, Mo) systems exhibit semiconducting behavior in both spin channels. Although undoped CeO₂ is a non-magnetic semiconductor. The band structure of these doped compounds was plotted and they exhibit direct band gap at the Fermi level (EF) in the majority and minority spin channels. In the magnetic properties, the doped atoms W and Mo play a vital role in increasing the magnetic moments of the supercell and the values of the total magnetic moment are found to be 1.998 μB for Ce₀.₇₅W₀.₂₅O₂ and to be 2.002 μB for Ce₀.₇₅Mo₀.₂₅O₂ compounds. Calculated results indicate that the magneto-electronic properties of the Ce₁₋ₓAₓO₂(A= W, Mo) oxides supply a new way to the experimentalist for the potential applications in spintronics devices.

Keywords: FP-LAPW, DFT, CeO₂, properties

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Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

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Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi

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Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.

Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis

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Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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Authors: Talat Baran

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Palladium-catalyzed Suzuki coupling reactions are powerful ways for synthesis of biaryls compounds and so far different palladium sources as have been used in catalyst systems. However, the high cost of the ligands using as support materials for palladium ion and so researchers have explored alternative low-cost support materials such as silica, cellule and zeolite. A natural polymer chitosan is suitable for support material because of it unique properties such as eco-friendly, renewable, abundant, low cost, biodegradable and it has free reactive -NH2 and –OH groups. Especially, pendant amino groups of chitosan can easily react with carbonyl groups of aldehyde or ketone by Schiff base formation and thus palladium ions can coordinate with imine groups of Schiff base. This purpose, in this study, firstly a new chitosan Schiff base supported palladium (II) catalyst was synthesized and its chemical structure was characterized with FT-IR, SEM/EDAX, XRD, TG-DTG, ICP-OES and magnetic moment techniques. Then catalytic performance of the catalyst was investigated in Suzuki cross coupling reactions under simple and fast microwave heating methods. Also, recycle activity of palladium catalyst was tested under optimum condition and the catalyst showed long life time. At the end of catalytic performance tests of chitosan supported palladium (II) catalysts indicated high turnover numbers, turnover frequency and selectivity with very small loading catalyst

Keywords: catalyst, chitosan, Schiff base, Suzuki coupling

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Authors: O. Smara, H. Dendougui, B. Legseir

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Atriplex halimus L. is particularly well adapted to arid and salt-affected areas. In this species, salinity resistance is often attributed to the presence of vesiculated hairs covering leaf surface and containing a large amount of salt. Atriplex halimus L. (Chenopodiaceae) is a perennial shrub native to the Mediterranean basin with excellent tolerance to drought and salinity. The species is present in semiarid to subhumid areas of the north Mediterranean and in arid zones from North Africa and the eastern Mediterranean. The main aim of this study was to identify a medicinal plant used in the Ouargla (Est-southern Algeria) for the treatment of several human pathologies. This plant is an important source for livestock in nitrogenous matter, it is an effective and relatively inexpensive tool in the fight against erosion and desertification and rehabilitation of degraded lands. Phytochemical investigation is applied to the majority of extracts of the powder of the aerial parts of Atriplex halimus L. Different chromatographic methods after liquid-liquid extraction are used; it is the thin layer chromatography (TLC) and paper using multiple systems and chemical revelations. This study followed by an evaluation by the phenol assay the Folin-Ciocalteu method, using gallic acid as a reference for phenols and quercetin for flavonols. Some polar extracts showed an interesting result better than the less polar extracts.

Keywords: Atriples halimus L., chenopodiaceae, flavonoids, phenols

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Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Isha Sharawat, R. P. Dahiya, T. R. Sreekrishnan

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One of the environmental challenges in India is urban wastewater management as regulations and infrastructural development has not kept pace with the urbanization and growing population. The quality of life of people is also improving with the rapid growth of the gross domestic product. This has contributed to the enhancement in the per capita water requirement and consumption. More domestic water consumption generates more wastewater. The scarcity of potable water is making the situation quite serious, and water supply has to be regulated in most parts of the country during summer. This requires elaborate and concerted efforts to efficiently manage the water resources and supply systems. In this article, a system dynamics modelling approach is used for estimating the water demand and wastewater generation in a district headquarter city of North India. Projections are made till the year 2035. System dynamics is a software tool used for formulation of policies. On the basis of the estimates, policy scenarios are developed for sustainable development of water resources in conformity with the growing population. Mitigation option curtailing the water demand and wastewater generation include population stabilization, water reuse and recycle and water pricing. The model is validated quantitatively, and sensitivity analysis tests are carried out to examine the robustness of the model.

Keywords: system dynamics, wastewater, water pricing, water recycle

Procedia PDF Downloads 265

Authors: M. Hisham, S. Cabemaiwai, S. Prasad, T. Dauvakatini, R. Ananthanarayanan

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A solenoid valve is an important part of many fluid systems. Its purpose is to regulate fluid flow in a machine. Due to the crucial role of the solenoid valve and its design intricacy, it is quite expensive to obtain in Fiji and is not manufactured locally. A concern raised by the local health industry is that the housing of the solenoid valve gets damaged when machines are continuously being used and this part of the valve is very costly to replace due to the lack of availability in Fiji and many other South Pacific region countries. This study explores the agile manufacturing of a solenoid coil housing using the Fused Deposition Modeling (FDM) process. An emergy study was carried out to analyze the feasibility and sustainability of producing the part locally after estimating a Unit Emergy Value (or emergy transformity) of 1.27E+05 sej/j for the electricity in Fiji. The total emergy of the process was calculated to be 3.05E+12 sej, of which a majority was sourced from imported services and materials. Renewable emergy sources contributed to just 16.04% of the total emergy. Therefore, the part is suitable to be manufactured in Fiji with a reasonable quality and a cost of $FJ 2.85. However, the loading on the local environment is found to be significant and therefore, alternative raw materials for the filament like recycled PET should be explored or alternative manufacturing processes may be analyzed before committing to fabricating the part using FDM in its analyzed state.

Keywords: emergy analysis, fused deposition modeling, solenoid valve housing, sustainable production

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Authors: R. A. C. K. Gunathilaka, P. T. D. Peiris, O. S. M. Jayawardane, S. M. A. I. Kulathunga

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Waste management is one of the predominant aspects of resource utilization and sustainability. The absence of a proper waste management system may lead to adverse troubles and catastrophic tragedies ultimately. Sri Lanka has faced different predicaments for a long time due to the unavailability of a systematic manner in the waste management process. The main objective of this research is to design an efficient waste management system for an urban area in Sri Lanka. The research was dispersed into three categories as biodegradable, non-biodegradable, and hazardous waste. Different waste materials were researched for each category by probing the entire process from the beginning to final disposal for perceiving the prevailing problems in the waste management system. The distinctive segment of this research is comparing efficient foreign waste management strategies with efficacious approaches on increasing public commitment to uncovering cognizable ways of implementing such a system in the Sri Lankan context. Waste management systems in Singapore, Japan, Malaysia, USA, Maldives, and China incorporated their exemplary plan of action on tackling the waste problem in diverse sectors were studied. Ultimately, three coherent models were proposed for each category pertaining to the concepts of circular economy and lean manufacturing from the inception to the final disposal of the waste. This research also includes concealed financial opportunities regarding waste management.

Keywords: circular economy, efficient waste management system, lean manufacturing, sustainability, urban area

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Dudu Ka Ruth Mkhize

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Adolescents are at the front and centre of poor mathematics performance in schools. Literature has concluded in some countries that there is a permanent and perpetual mathematics crisis in schools of the persistent poor performance in mathematics by teens. There is no shortage of interventions and research to solve this problem. However, none has capitalised on the cognitive prowess of adolescents, which was revealed at the turn of the century by the introduction of neuroimaging technologies such as structural and functional magnetic resonance imaging (sMRI and fMRI). This research found that brain growth during adolescence results in enhanced cognitive abilities essential for mathematics learning. This paper is based on the four-year case study of rural high school adolescents who had a negative attitude towards mathematics and hence were failing mathematics. But through a ten-day intervention where teaching revolved around invoking their cognitive ability, their attitude and motivation for mathematics changed for the better. The paper concludes that despite educational psychology being part of teacher education as well as education systems, there are numerous overlooked gems of psychological theories which have the potential to enhance academic achievement for youth in schools. A recommendation is made to take cues from positive psychology, whose establishment was a rejection of the dominance of the disease model in psychology. Similarly, the general perspective of poor mathematics performance can take a u-turn towards the cognitive ability acquired by adolescents because of their developmental stage.

Keywords: adolescence, cognitive growth, mathematics performance

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Authors: P. Okoro Ugo Chigozie, P. A. Igbojekwe, E. N. Ukabuilu

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Tourism and terrorism experiences are best viewed as dynamic, complex systems with extreme diverse consequences on any nation’s economy. Tourism is one of the biggest industries in the world and one of the economical sectors which grows rapidly; tourism has positive impact on the nation’s economy. Terrorism is the method or the theory behind the method whereby an organized group or party seeks to achieve its avowed aims chiefly through the systematic use of violence; the consequences of terrorism on tourist destinations are inescapable and can be profound. Especially, it threatens the attractiveness of a tourist destination and strips the competitiveness of that destination. Destination’s vulnerability to politically motivated violence not only retracts tourists, but threatens sustainable tourism development. This paper examines the activities of the Jamaata Ahlis Sunna Liddaawati -an Islamic sect popularly known as Boko Haram – and its impact on sustainable tourism development in the Nigeria state. Possible triggers of this insurgency and potentially evolving measure against its influence on sustainable tourism including, strong image management of the tourism industry, feasible tourist safety policy, viable anti-terrorism measures, proactive respond to the challenge of terrorism, reinforcement of the legitimate frameworks and irrevocable penalty against menace of corruption; are discussed in this paper, as limiting the effects of insurgency on the attractiveness of Nigeria as safe tourists destination.

Keywords: Nigeria, terrorism, sustainable tourism development, corruption and competitiveness

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Authors: Mona Mahmoud Abou Samra, Alaa Hamed Salama, Ghada Awad, Soheir Said Mansy

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Proniosomes are well documented for topical drug delivery and preferred over other vesicular systems because they are biodegradable, biocompatible, non-toxic, possess skin penetration ability and prolong the release of drugs by acting as depot in deeper layers of skin. Proniosome drug delivery was preferred due to improved stability of the system than niosomes. The present investigation aimed at formulation development and performance evaluation of proniosomal gel as a vesicular drug carrier system for antifungal drug tolnaftate. Proniosomes was developed using different nonionic surfactants such as span 60 and span 65 with cholesterol in different molar ratios by the Coacervation phase separation method in presence or absence of either lecithin or phospholipon 80 H. Proniosomal gel formulations of tolnaftate were characterized for vesicular shape & size, entrapment efficiency, rheological properties and release study. The effect of surfactants and additives on the entrapment efficiency, particle size and percent of drug released was studied. The selected proniosomal formulations for topical delivery of tolnaftate was subjected to a microbiological study in male rats infected with Trichophyton rubrum; the main cause of Tinea Pedis compared to the free drug and a market product and the results was recorded.

Keywords: fungal infection, proniosome, tolnaftate, trichophyton rubrum

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Authors: Jakub Adamec, Svatava Janouskova, Tomas Hak

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The necessity of sustainable housing is explicitly embedded in ‘The 2030 agenda for sustainable development’, in particular, goal 11 ‘sustainable cities and communities’. Every UN member state is obligated to implement strategies from the agenda, including a strategy for sustainable housing into the practice in the local context. As shown in many countries, the lack of knowledge represses the adaptation process of sustainable strategies by governments. Hence, this study explores the concept of sustainable housing within the Czech Republic. The research elaborates on this term, and its current definition concerning ‘Geneva UN Charter on Sustainable Housing’. To this day, the charter represents the most comprehensive framework for a sustainable housing concept. Researchers conducted a comparative analysis of 38 international and 195 Czech national strategic documents. As a result, the charter‘s and strategic documents‘ goals were interconnected, identifying the most represented targets (e.g. improved environmental and energy performance of dwellings, resilient urban settlements which use renewable energy, and sustainable and integrated transport systems). The research revealed, even though the concept of sustainable housing is still dominated by environmental aspects, that social aspects significantly increased its importance. Additionally, this theoretical framework will serve as a foundation for the sustainable housing index development for the Czech Republic.

Keywords: comparative analysis, Czech national strategy, Geneva un charter, sustainable housing, urban theory

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Authors: Waleed Basuliman

Abstract:

Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

Abstract:

Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: indoor localization, digital forensics, fingerprinting, tracking and cloud

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Authors: Gopikrishnan, Bharathiraja, Boopalan, Jensin Joshua

Abstract:

The Pitot static tube has proven their values and practicability in measuring velocity of fluids for many years. With the aim of extensive usage of such Pitot tube systems, one of the major enabling technologies is to use the design and fabricate a high sensitive pitot tube for the purpose of calibration of the subsonic wind tunnel. Calibration of wind tunnel is carried out by using different instruments to measure variety of parameters. Using too many instruments inside the tunnel may not only affect the fluid flow but also lead to drag or losses. So, it is essential to replace the different system with a single system that would give all the required information. This model of high sensitive Pitot tube has been designed to ease the calibration process. It minimizes the use of different instruments and this single system is capable of calibrating the wind tunnel test section. This Pitot static tube is completely digitalized and so that the velocity data`s can be collected directly from the instrument. Since the turbulence factors are dependent on velocity, the data’s that are collected from the pitot static tube are then processed and the level of turbulence in the fluid flow is calculated. It is also capable of measuring the pressure distribution inside the wind tunnel and the flow angularity of the fluid. Thus, the well-designed high sensitive Pitot static tube is utilized in calibrating the tunnel and also for the measurement of turbulence.

Keywords: pitot static tube, turbulence, wind tunnel, velocity

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Authors: Christiana Ebobo

Abstract:

Cybercrime consists of numerous crimes that are perpetrated on the internet on daily basis. The forms include but not limited to Identity theft, Pretentious dating, Desktop counterfeiting, Internet chat room, Cyber harassment, Fraudulent electronic mails, Automated Teller Machine Spoofing, Pornography, Piracy, Hacking, Credit card frauds, Phishing and Spamming. The general term used among the youths for this type of crime in Nigeria is ‘Yahoo Yahoo’. Cybercrime is on the increase among the youths at all levels as such this study aims at examining the impact of cybercrime on youth development in Nigeria. The study examines the impact of cybercrime on youths’ academic performance, integrity, employment and religious practices. The study is a survey which made use of questionnaire and focus group discussion among 150 randomly selected youths in Gwagwalada LCDA, Federal Capital Territory, Nigeria. The study adopts the systems theory as its theoretical framework. The study also adopts the simple frequency table and percentage for its data analysis. The study reveals that cybercrime has eaten deep into the minds of some youths and some of them are practicing diabolic means to succeed in it. It is also reveals that majority (68%) of the respondents believe that cybercrime impacts negatively on youths’ academic performance in Nigeria. The major recommendation of this study is that cybercrime offenders should be treated like armed robbers in order to discourage other youths from getting involved in it.

Keywords: armed robber, cybercrime, integrity, youth

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Authors: Shahrokh Barati, Reza Ramezani

Abstract:

Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

Abstract:

This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

Procedia PDF Downloads 178